Background: In the phase III IMpassion130 trial, combining atezolizumab with first-line nanoparticle albumin-boundpaclitaxel for advanced triple-negative breast cancer (aTNBC) showed a statistically significant progression-free survival (PFS) benefit in the intention-to-treat (ITT) and programmed death-ligand 1 (PD-L1)-positive populations, and a clinically meaningful overall survival (OS) effect in PD-L1-positive aTNBC. The phase III KEYNOTE-355 trial adding pembrolizumab to chemotherapy for aTNBC showed similar PFS effects. IMpassion131 evaluated first-line atezolizumabepaclitaxel in aTNBC. Patients and methods: Eligible patients [no prior systemic therapy or 12 months since (neo)adjuvant chemotherapy] were randomised 2:1 to atezolizumab 840 mg or placebo (days 1, 15), both with paclitaxel 90 mg/m 2 (days 1, 8, 15), every 28 days until disease progression or unacceptable toxicity. Stratification factors were tumour PD-L1 status, prior taxane, liver metastases and geographical region. The primary endpoint was investigator-assessed PFS, tested hierarchically first in the PD-L1-positive [immune cell expression 1%, VENTANA PD-L1 (SP142) assay] population, and then in the ITT population. OS was a secondary endpoint. Results: Of 651 randomised patients, 45% had PD-L1-positive aTNBC. At the primary PFS analysis, adding atezolizumab to paclitaxel did not improve investigator-assessed PFS in the PD-L1-positive population [hazard ratio (HR) 0.82, 95% confidence interval (CI) 0.60-1.12; P ¼ 0.20; median PFS 6.0 months with atezolizumabepaclitaxel versus 5.7 months with placeboepaclitaxel]. In the PD-L1-positive population, atezolizumabepaclitaxel was associated with more favourable unconfirmed best overall response rate (63% versus 55% with placeboepaclitaxel) and median duration of response (7.2 versus 5.5 months, respectively). Final OS results showed no difference between arms (HR 1.11, 95% CI 0.76-1.64; median 22.1 months with atezolizumabepaclitaxel versus 28.3 months with placeboe paclitaxel in the PD-L1-positive population). Results in the ITT population were consistent with the PD-L1-positive population. The safety profile was consistent with known effects of each study drug. Conclusion: Combining atezolizumab with paclitaxel did not improve PFS or OS versus paclitaxel alone. ClinicalTrials.gov: NCT03125902.

Cancer is one of the most common diseases afflicting people globally. New therapeutic approaches are needed due to the complexity of cancer as a disease. Many current treatments are very toxic and have modest efficacy at best. Increased understanding of tumor biology and immunology has allowed the development of specific immunotherapies with minimal toxicity. It is important to highlight the performance of monoclonal antibodies, immune adjuvants, vaccines and cell-based treatments. Although these approaches have shown varying degrees of clinical efficacy, they illustrate the potential to develop new strategies. Targeted immunotherapy is being explored to overcome the heterogeneity of malignant cells and the immune suppression induced by both the tumor and its microenvironment. Nanodelivery strategies seek to minimize systemic exposure to target therapy to malignant tissue and cells. Intracellular penetration has been examined through the use of functionalized particulates. These nano-particulate associated medicines are being developed for use in imaging, diagnostics and cancer targeting. Although nano-particulates are inherently complex medicines, the ability to confer, at least in principle, different types of functionality allows for the plausible consideration these nanodelivery strategies can be exploited for use as combination medicines. The development of targeted nanodelivery systems in which therapeutic and imaging agents are merged into a single platform is an attractive strategy. Currently, several nanoplatform-based formulations, such as polymeric nanoparticles, micelles, liposomes and dendrimers are in preclinical and clinical stages of development. Herein, nanodelivery strategies presently investigated for cancer immunotherapy, cancer targeting mechanisms and nanocarrier functionalization methods will be described. We also intend to discuss the emerging nano-based approaches suitable to be used as imaging techniques and as cancer treatment options.

IntroductionInterval cancers are tumors arising after a negative screening episode and before the next screening invitation. They can be classified into true interval cancers, false-negatives, minimal-sign cancers, and occult tumors based on mammographic findings in screening and diagnostic mammograms. This study aimed to describe tumor-related characteristics and the association of breast density and tumor phenotype within four interval cancer categories.MethodsWe included 2,245 invasive tumors (1,297 screening-detected and 948 interval cancers) diagnosed from 2000 to 2009 among 645,764 women aged 45 to 69 who underwent biennial screening in Spain. Interval cancers were classified by a semi-informed retrospective review into true interval cancers (n = 455), false-negatives (n = 224), minimal-sign (n = 166), and occult tumors (n = 103). Breast density was evaluated using Boyd’s scale and was conflated into: <25%; 25 to 50%; 50 to 75%; >75%. Tumor-related information was obtained from cancer registries and clinical records. Tumor phenotype was defined as follows: luminal A: ER+/HER2- or PR+/HER2-; luminal B: ER+/HER2+ or PR+/HER2+; HER2: ER-/PR-/HER2+; triple-negative: ER-/PR-/HER2-. The association of tumor phenotype and breast density was assessed using a multinomial logistic regression model. Adjusted odds ratios (OR) and 95% confidence intervals (95% CI) were calculated. All statistical tests were two-sided.ResultsForty-eight percent of interval cancers were true interval cancers and 23.6% false-negatives. True interval cancers were associated with HER2 and triple-negative phenotypes (OR = 1.91 (95% CI:1.22-2.96), OR = 2.07 (95% CI:1.42-3.01), respectively) and extremely dense breasts (>75%) (OR = 1.67 (95% CI:1.08-2.56)). However, among true interval cancers a higher proportion of triple-negative tumors was observed in predominantly fatty breasts (<25%) than in denser breasts (28.7%, 21.4%, 11.3% and 14.3%, respectively; <0.001). False-negatives and occult tumors had similar phenotypic characteristics to screening-detected cancers, extreme breast density being strongly associated with occult tumors (OR = 6.23 (95% CI:2.65-14.66)). Minimal-sign cancers were biologically close to true interval cancers but showed no association with breast density.ConclusionsOur findings revealed that both the distribution of tumor phenotype and breast density play specific and independent roles in each category of interval cancer. Further research is needed to understand the biological basis of the overrepresentation of triple-negative phenotype among predominantly fatty breasts in true interval cancers.

Molecular modeling techniques provide a powerful tool to study the properties of molecules and their interactions at the molecular level. The use of computational techniques to predict interaction patterns and molecular properties can inform the design of drug delivery systems and therapeutic agents. Dendrimers are hyperbranched macromolecular structures that comprise repetitive building blocks and have defined architecture and functionality. Their unique structural features can be exploited to design novel carriers for both therapeutic and diagnostic agents. Many studies have been performed to iteratively optimise the properties of dendrimers in solution as well as their interaction with drugs, nucleic acids, proteins and lipid membranes. Key features including dendrimer size and surface have been revealed that can be modified to increase their performance as drug carriers. Computational studies have supported experimental work by providing valuable insights about dendrimer structure and possible molecular interactions at the molecular level. The progress in computational simulation techniques and models provides a basis to improve our ability to better predict and understand the biological activities and interactions of dendrimers. This review will focus on the use of molecular modeling tools for the study and design of dendrimers, with particular emphasis on the

Intestinal pathogens use the host's excessive inflammatory cytokine response, designed to eliminate dangerous bacteria, to disrupt epithelial gut wall integrity and promote their tissue invasion. We sought to develop a non-antibiotic-based approach to prevent this injury. Molecular docking studies suggested that glycosylated dendrimers block the TLR4-MD-2-LPS complex, and a 13.6 kDa polyamidoamine (PAMAM) dendrimer glucosamine (DG) reduced the induction of human monocyte interleukin (IL)-6 by Gram-negative bacteria. In a rabbit model of shigellosis, PAMAM-DG prevented epithelial gut wall damage and intestinal villous destruction, reduced local IL-6 and IL-8 expression, and minimized bacterial invasion. Computational modelling studies identified a 3.3 kDa polypropyletherimine (PETIM)-DG as the smallest likely bioactive molecule. In human monocytes, high purity PETIM-DG potently inhibited Shigella Lipid A-induced IL-6 expression. In rabbits, PETIM-DG prevented Shigella-induced epithelial gut wall damage, reduced local IL-6 and IL-8 expression, and minimized bacterial invasion. There was no change in β-defensin, IL-10, interferon-β, transforming growth factor-β, CD3 or FoxP3 expression. Small and orally delivered DG could be useful for preventing gut wall tissue damage in a wide spectrum of infectious diarrhoeal diseases.–>See accompanying article http://dx.doi.org/10.1002/emmm.201201668